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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

PyARC Status Report: New Integrations and Upgrades to the Fast Reactor Analysis Workflow Management Tool

PyARC was initially developed as an open source tool to support fast reactor analyses using the Argonne Reactor Computation (ARC) code suite as a part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench initiative in FY17. The goal of this initiative is to provide a common user interface for model generation, real-time validation, execution, output processing, and visualization for all integrated codes. This is accomplished through the reliance on tools available in the Workbench framework and runtime environment. While initially developed to support the ARC codes, PyARC was extended in FY22 to wrap other NEAMS and non-ARC codes, including Griffin and OpenMC, in the supported other neutronics workflows, and support users in the adoption of NEAMS-supported high fidelity analysis codes. Most recently, NUBOW-3D, a recently adopted ARC code, was integrated to support reactor bowing calculations as well. Integration of these codes into the NEAMS Workbench directly benefits the advanced reactor modeling community by: • Providing a set of controlled, maintained, documented and validated scripts to generate inputs, which promotes best practices, reduces the learning curve, and facilitates project collaboration. • Improving the user experience: the Workbench interface provides assistance for building an input through auto-completion, real-time validation, document navigation, and geometry and results visualization. • Automating complex calculations and workflows for reactor analysis. • Helping users transition to using high-fidelity NEAMS codes along-side the ARC codes. In FY22, a progress report was published that described the state of each of the tools integrated into PyARC. Since then, there have been many enhancements and upgrades to the existing integrations as well as entirely new code integrations as well. This report details all new integrations and major developments in PyARC since the version 2.0.0 release highlighted in the FY22 report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

The FRIB Decay Station: New Horizons with Rare Isotopes

In May 2022, the Facility for Rare Isotope Beams (FRIB), located on the campus of Michigan State University (MSU), began delivering exotic isotopes to an international community of scientists. New discoveries are now being reported from radioactive decay of neutron-rich nuclei near N = 20 and N = 28.FRIB is expected to produce roughly 80% of the unstable or radioactive isotopes predicted to exist up to uranium (Z = 92). The new user facility is supported by the U.S. Department of Energy, and it is operated by MSU. A high-power superconducting linear accelerator, shaped like a paper-clip, drives the production of these rare isotopes by colliding stable nuclei moving at half the speed of light with a rotating, water-cooled graphite tar-get. These collisions cause the primary stable beam to fragment into a wide variety of unstable nuclei, which can be subsequently filtered through a multistage magnetic separator, the Advanced Rare Isotope Separator, and transported to one of several experimental stations. The FRIB Decay Station initiator (FDSi) (see Figure 1) was developed to enable comprehensive radio-active decay studies of the exotic nuclei produced by FRIB and it was used in the first two experiments in 2022. Further, the FDSi is a highly reconfigurable multidetector system with two focal planes (FP1 for discrete spectroscopy and FP2 for total absorption spectroscopy) that can be optimized for the specific science goals of each experiment. It is designed, built, and operated by a community of users with the sup-port of U.S. funding agencies, including the Department of Energy and National Science Foundation.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

ArborX

ArborX library tackles a problem of efficiently finding geometric objects that are close in space. Variations of this problem, such as finding the nearest neighbors of a point, or finding all objects within a certain distance, are inherent components of applications in many fields. The data may be large so that solving the problem efficiently may require significant computational resources, such as multiple processors or accelerators such as general purpose GPUs. ArborX' main advantage in its ability to solve large problems efficiently utilizing a combination of distributed and on-node parallelism. ArborX can be run efficiently on a wide variety of hardware, including GPUs from different vendors, which distinguishes it from other available libraries which typically choose only few of these. The other advantage is that it supports both types of user problems: spatial problems (useful for intersections and finding objects within certain distance), and nearest neighbor problems. ArborX also supports flexible interface in its interaction with a user. Particularly, it allows a user to call user's own function on a positive match, a functionality not rarely available in other libraries. ArborX implements construction and traversal algorithms using efficient tree structures, such as bounding volume hierarchy (BVH). At its core, it uses linear BVH for its low construction cost and sufficient quality. ArborX is written using C++, and is parallelized using the message passing interface (MPI) for the distributed communication, and the Kokkos library for on-node parallelism. This approach allows ArborX to be run on a wide variety of hardware, from common laptops and desktops to supercomputers while using the same codebase. ArborX also implements several advanced algorithms using geometric search, such as density-based clustering algorithm DBSCAN.

ECP↗
DOE OSTI2025

ArborX 2.0

ArborX library tackles a problem of efficiently finding geometric objects that are close in space. Variations of this problem, such as finding the nearest neighbors of a point, or finding all objects within a certain distance, are inherent components of applications in many fields. The data may be large so that solving the problem efficiently may require significant computational resources, such as multiple processors or accelerators such as general purpose GPUs. ArborX' main advantage in its ability to solve large problems efficiently utilizing a combination of distributed and on-node parallelism. ArborX can be run efficiently on a wide variety of hardware, including GPUs from different vendors, which distinguishes it from other available libraries which typically choose only few of these. The other advantage is that it supports both types of user problems: spatial problems (useful for intersections and finding objects within certain distance), and nearest neighbor problems. ArborX also supports flexible interface in its interaction with a user. Particularly, it allows a user to call user's own function on a positive match, a functionality not rarely available in other libraries. ArborX implements construction and traversal algorithms using efficient tree structures, such as bounding volume hierarchy (BVH). At its core, ArborX uses linear BVH for its low construction cost and sufficient quality. ArborX implements both spatial and nearest-neighbor traversal algorithms. ArborX also provides several clustering algorithms (minimum spanning tree, DBSCAN, HDBSCAN*), interpolation using minimum least squares and ray tracing. ArborX is written using C++, and is parallelized using the message passing interface (MPI) for the distributed communication, and the Kokkos library for on-node parallelism. This approach allows ArborX to be run on a wide variety of hardware, from common laptops and desktops to supercomputers while using the same codebase.

Prokopenko, Andrey [Oak Ridge National Laboratory ↗
DOE OSTI2020

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

The execution of agent-based simulations (ABSs) on hardware accelerator devices such as graphics processing units (GPUs) has been shown to offer great performance potentials. However, in heterogeneous hardware environments, it can become increasingly difficult to find viable partitions of the simulation and provide implementations for different hardware devices. To automate this process, we present OpenABLext, an extension to OpenABL, a model specification language for ABSs. By providing a device-aware OpenCL backend, OpenABLext enables the co-execution of ABS on heterogeneous hardware platforms consisting of central processing units, GPUs, and field programmable gate arrays (FPGAs).We present a novel online dispatching method that efficiently profiles partitions of the simulation during run-time to optimize the hardware assignment while using the profiling results to advance the simulation itself. In addition, OpenABLext features automated conflict resolution based on user-specified rules, supports graph-based simulation spaces, and utilizes an efficient neighbor search algorithm. We show the improved performance of OpenABLext and demonstrate the potential of FPGAs in the context of ABS. We illustrate how co-execution can be used to further lower execution times. OpenABLext can be seen as an enabler to tap the computing power of heterogeneous hardware platforms for ABS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Integer Sum Reduction with OpenMP on an AMD MI100 GPU

Sum reduction is a primitive operation in parallel computing. Device offload support allows a user to use OpenMP directives to take advantage of a highly capable GPU. In this paper, we present the integer sum reduction annotated with the OpenMP directives and evaluate the performance impacts of tunable parameters with the AOMP and GCC compilers on an AMD MI100 GPU. In addition, we explain the implementations of the OpenMP reduction by the compilers. Sweeping over the pruned parameter space, we find that the speedup is approximately 20 with AOMP, and the reduction performance using AOMP is approximately 11% higher than that using GCC. However, the OpenMP offload performance is approximately 30% lower compared to the performance of the reductions written with rocThrust or hipCUB.

Jin, Zheming↗
DOE OSTI2025

Operating Klystrons at the Spallation Neutron Source – Two Decades of Perspective

Klystron amplifiers have been operated at the Spallation Neutron Source (SNS) in support of the user program since 2006. SNS tubes have amassed over 100,000 hours of high-voltage and filament-on time providing a significant source of operational statistics for high power, high-duty klystrons. Additionally, the SNS Radiofrequency (RF) Systems Group has developed operational methods to mitigate specific reliability challenges, such as cathode arcing and output power instability. Despite much progress, many of these challenges persist, prompting the SNS to update the procedures used for klystron processing as well as develop a higher throughput test stand.

Moss, John [ORNL] (ORCID:0009000085988916)↗
DOE OSTI2023

A 50 kA Superconducting Transformer for the Upcoming High-Field High-Current Testing Station at the BNL

Brookhaven national laboratory is upgrading its existing user facility to support R&D for High Energy Physics (HEP) and Fusion Energy Sciences (FES). The goal of this upgrade is to host the testing of the superconducting cables, conductors, joints and insert coils under high magnetic field (10 T), with currents up to 50 kA (present limit 20 kA) and at temperatures varying from 4 K to 40 K. To provide a current up to 50 kA to the sample, a superconducting core-less transformer is under construction. The superconducting transformer would additionally reduce the heat loss at the current leads at high currents. The SC transformer consists of two coaxial coils. The primary coil is inside the secondary coil. The primary coil consists of 3048 turns of rectangular wires (1.91 mm x 1.27 mm), wound in 24 layers. The secondary coil consists of 13 turns of the secondary cable (18.35 mm x 5.96 mm), wound in one layer. The parameters of the transformer are chosen to satisfy the space restrictions while using the available conductor. Here this paper presents the design of the 50-kA transformer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Cross-facility science with the Superfacility Project at LBNL

As data sets from DOE user science facilities grow in both size and complexity there is an urgent need for new capabilities to transfer, analyze and manage the data underlying scientific discoveries. LBNL's Superfacility project brings together experimental and observational research instruments with computational and network facilities at the National Energy Research Scientific Computing Center (NERSC) and the Energy Sciences Network (ESnet) with the goal of enabling user science. Here, we report on recent innovations in the Superfacility project, including advanced data management, API-based automation, real-Time interactive user interfaces, and supported infrastructure for 'edge' services.

Enders, B↗
DOE OSTI2020

MCNP6 Source Primer: Release 1.0

This document contains examples of MCNP general source usage to support the MCNP6 User’s Manual. The examples range from basic to advanced sources with different applications. There are also examples of how MCNP can fail and warnings for the users to look for at the output to ensure proper results are being created. The overall aim of this document is to provide solid examples of how to define sources with MCNP as well as how to verify the sources are setup properly. The reasoning for needing such complex sources is not discussed in the present work. Also, this document is not meant to be exhaustive of every MCNP source option and combinations of source options possible. However, it is intended to frequently update this document with new source examples provided by users. Please feel free to contact the MCNP6 development team to learn about how to submit a new or updated source example. Please include “General Sources Primer” in the subject line to route the request to the appropriate developers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Seer: Using Mochi for In Situ Analysis

Seer is an in situ framework that allows steering of in situ analysis. Seer works with other existing in situ software such as ParaView Catalyst. It supports multi-user analysis

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Science of Scientific Software Development and Use

Increasingly powerful and affordable computing has revolutionized scientific and scholarly discovery across a broad range of fields. Computing relies on software, which has been rapidly growing in scope, diversity, and complexity. At the same time, the methods, processes, and tools used to produce and utilize this essential software are often ad hoc, and the study and improvement of them is often done without the benefit of direct funding or prioritization. Consequently, concerns are growing about the productivity of the developers and users of scientific software, its sustainability, and the trustworthiness of the results that it produces. The US Department of Energy Office of Science (DOE-SC) is at the forefront of modern software-enabled scientific discovery across numerous areas of computational, experimental, and observational science, including major investments in national user facilities that support these activities. In December 2021, the DOE-SC Office of Advanced Scientific Computing Research (ASCR) convened a workshop on basic research needs for the Science of Scientific Software Development and Use (SSSDU). Through keynote presentations, lightning talks, and breakout groups, participants discussed the current practice of software development, maintenance, evolution, and use, and considered how the scientific method could be used to examine these practices and develop more evidence-based approaches to enhance the impact of software and computing on all areas of science. Workshop participants identified three priority research directions (PRDs) and three important crosscutting themes that center on the following overarching insight: software has become an essential part of modern science that impacts new discovery, policy, and technological development. To have full confidence in science delivered via software, we must improve the processes and tools that help us create and use it, and this enhancement requires a deep understanding of the diverse array of teams and individuals doing the work. The full workshop report will be available at https://doi.org/10.2172/1846009.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Basic Research Needs in The Science of Scientific Software Development and Use: Investment in Software is Investment in Science

Increasingly powerful and affordable computing has revolutionized scientific and scholarly discovery across a broad range of fields. Computing relies on software, which has been rapidly growing in scope, diversity, and complexity. At the same time, the methods, processes, and tools used to produce and utilize this essential software are often ad hoc, and the study and improvement of them are often done without the benefit of direct funding or prioritization. Consequently, concerns are growing about the productivity of the developers and users of scientific software, its sustainability, and the trustworthiness of the results that it produces. Increased investment, especially in the characterization and improvement of how scientific software is developed and used, is important for sustaining and improving the impact of software as the scope and complexity of scientific efforts expand. Without this investment, we face the risk of diminishing returns on our software investments because the demands for increased functionality, usability, reliability, and more will not be sufficiently met. The US Department of Energy Office of Science (DOE/SC) is at the forefront of modern software-enabled scientific discovery across numerous areas of computational, experimental, and observational science, including major investments in national user facilities that support these activities. For many years, DOE/SC software investments have provided tremendous value to the scientific community. We want to continue and further improve the value of DOE/SC software efforts by using a scientific approach to understanding and improving how scientific software is developed and used. In December 2021, the DOE/SC Office of Advanced Scientific Computing Research (ASCR) convened a workshop on basic research needs for the Science of Scientific-Software Development and Use (SSSDU). Through keynote presentations, lightning talks, and breakout groups, which built on insights from 124 pre-workshop position papers, participants discussed the current practice of software development, maintenance, evolution, and use, and considered how the scientific method could be used to examine these practices and develop more evidence-based approaches to enhance the impact of software and computing on all areas of science. Workshop participants identified three priority research directions (PRDs) and three important crosscutting themes that center on the following overarching insight: Software has become an essential part of modern science, impacting discoveries, policy, and technological development. To maintain and improve confidence in science delivered via software, we must improve the processes and tools that help us create and use software, and this enhancement requires a deep understanding of the diverse array of teams and individuals doing the work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Applying the Risk Management Framework: The Distributed Energy Resource Risk Manager

As part of a multiyear effort, the National Renewable Energy Laboratory (NREL) has dedicated resources to understand and identify cybersecurity weaknesses in distributed energy resources (DERs) by performing assessments. Due to a lack of standardization and rapidly increasing adoption of DERs, there is a critical need to address cybersecurity needs for DER systems in an interactive way. Furthermore, federal agencies, which are required to obtain an authority to operate, are challenged by the complexities of including their DERs. To help meet this need, in early 2020, NREL released the Distributed Energy Resources Cybersecurity Framework (DERCF) and accompanying Web application. This process is supported by the Risk Management Framework (RMF) developed by the National Institute of Standards and Technology. This project, referred to as the DERCF RMF application, expands on the existing DERCF work to include methods that support walking a user through the seven RMF steps. The tool will be available for download at no cost from [link ]. The purpose of this paper is to describe the steps the DERCF team at NREL took to understand Steps 1-5 of the RMF process. Additionally, this document will identify future work on the first five steps as well as a plan for Steps 6 and 7.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

MTA Secondary Beamline Production and Optics Optimization

A new secondary beamline was recently installed in the MeV Test Area (MTA) with the objective of enhancing mu+/mu- production by factors of 3/8 by using a tungsten target versus the conventional graphite production target using the 400 MeV Fermilab proton Linac beam. Ultra-low energy muon beams can support world-class physics experiments for fundamental muon measurements, sensitive searches for symmetry violation, and precision tests of theory. Extensive production studies have confirmed higher muon yield from heavy targets (tungsten vs carbon), but also, surprisingly, showed significant differences in production fluence and energy spectrum between modern hadronic models (GENIEhad) and between GEANT and MCNP. Studies are also underway towards a high-efficiency source of muonium by stopping the mu+ beam in superfluid helium. Muon fluxes can be measured at MTA including using higher-Z and novel target geometries to test hadronic and production models which are critical to understanding ongoing experiments (Mu2e) and will significantly impact the planning of future HEP experiments and planning PIP II facilities. The MTA beamline will additionally support a broad user muon test beam for future experiments and R&D.

Ahmed, Shiza↗
DOE OSTI2024

Desert-Urban SysTem IntegratEd AtmospherIc Monsoon (DUSTIEAIM) in the Southwestern United States

Phoenix, Arizona, is the fifth-largest city in the United States with about 1.6 million residents. It is also considered to be the hottest major city in the country, having set a record of 31 consecutive days with temperatures above 110 F (43 C) in summer 2023. Phoenix depends on the Colorado River for over a third of its water supply, but there are questions about how much water will eventually be available to serve the rapidly growing metropolitan area, especially in such extreme heat. Current earth system models struggle to accurately capture precipitation in the Southwestern United States, especially in relation to the summertime North American Monsoon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

RAG for FLAG: AI Assistance for a Physics Code

Artificial intelligence (AI) has quickly become an important tool in scientific research, where significant efforts are underway to develop tools that will expedite the research process. One area of particular impact is scientific software, which can be particularly complex, and therefore time consuming to learn and use effectively. AI assistants are increasingly helping to streamline the process by performing tasks such as interactively answering user questions or suggesting solutions. Los Alamos National Laboratory (LANL) develops several advanced scientific codes, such as FLAG, which can be used to run multiphysics simulations. With this study, our goal was to develop an AI assistant for FLAG that could help make the process of understanding the software and running physics simulations more efficient. To develop an AI assistant for FLAG, we used a method called retrieval-augmented generation (RAG), which is a technique that uses information from relevant data sources to enhance the accuracy of large language models (LLMs). We used the FLAG user manual and other FLAG documentation as the knowledge base for the RAG system. When a user provides a query, RAG retrieves relevant sections from the knowledge base in response, then uses those excerpts to generate grounded and contextually rich answers. We found that our AI assistant was able to provide context aware answers and source references to user queries. To evaluate performance, we developed a set of 40 benchmark questions and compared the accuracy of the responses to those of two standard LLMs without retrieval. Our AI assistant significantly outperformed the standard LLMs at answering FLAG-related questions, with an 82.5% accuracy rate, compared to 47.5% for both of the standard LLMs. This has the potential to make the process of learning and using FLAG much easier, especially for new users. Ultimately, it supports LANL’s broader mission by empowering scientists and engineers to focus more on discovery and analysis rather than on navigating complex software systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

LANSCE Accelerator Modernization Project Conceptual Design Report

The accelerator complex now known as the Los Alamos Neutron Science Center (LANSCE) began operation in 1972 as LAMPF, the Los Alamos Meson Production Facility. In the intervening 53 years, the complex has been expanded in capability several times, both in terms of its accelerator performance and the user facilities it supports.

43 PARTICLE ACCELERATORS↗